Invention Grant
US08576690B2 Systems and methods for implementing a multi-sensor receiver in a DSM3 environment
有权
用于在DSM3环境中实现多传感器接收器的系统和方法
- Patent Title: Systems and methods for implementing a multi-sensor receiver in a DSM3 environment
- Patent Title (中): 用于在DSM3环境中实现多传感器接收器的系统和方法
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Application No.: US13051906Application Date: 2011-03-18
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Publication No.: US08576690B2Publication Date: 2013-11-05
- Inventor: Laurent Pierrugues , Laurent Francis Alloin , Amitkumar Mahadevan
- Applicant: Laurent Pierrugues , Laurent Francis Alloin , Amitkumar Mahadevan
- Applicant Address: US CA Fremont
- Assignee: Ikanos Communications, Inc.
- Current Assignee: Ikanos Communications, Inc.
- Current Assignee Address: US CA Fremont
- Agency: Pillsbury Winthrop Shaw Pittman LLP
- Agent Mark J. Danielson
- Main IPC: H04J1/12
- IPC: H04J1/12

Abstract:
In accordance with one embodiment, a method is implemented in a vectored system for improving a signal-to-noise ratio (SNR) of a far end transmitted signal on a victim line in the system. The method comprises mitigating, by the vectored system, self-induced far-end crosstalk (self-FEXT) on the victim line based on self-FEXT mitigation coefficients and receiving, by a second sensor, information relating to at least one of: self-FEXT of the vectored system, external noise, and the far end transmitted signal. The method further comprises learning, at the second sensor, coefficients relating to self-FEXT coupling into the second sensor and removing self-FEXT from the second sensor based on the learned coefficients. Upon removal of self-FEXT from the second sensor, a linear combiner configured to combine information relating to the victim line and the second line is learned. The method further comprises applying the learned linear combiner and readjusting the self-FEXT mitigation coefficients to remove any residual self-FEXT on the victim line after application of the learned linear combiner.
Public/Granted literature
- US20110235759A1 Systems and Methods for Implementing a Multi-Sensor Receiver in a DSM3 Environment Public/Granted day:2011-09-29
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